Overview

Brought to you by YData

Dataset statistics

Number of variables158
Number of observations10000
Missing cells110004
Missing cells (%)7.0%
Total size in memory7.2 MiB
Average record size in memory760.0 B

Variable types

Numeric69
Text6
Boolean72
Unsupported11

Alerts

process_pmf_development_methodologies has constant value "agile development" Constant
project_prf_application_group_infrastructure_software has constant value "0" Constant
project_prf_application_group_real_time_application has constant value "0" Constant
tech_tf_clientserver_description_browser_server_architecture has constant value "0.0" Constant
tech_tf_clientserver_description_client_server has constant value "0.0" Constant
tech_tf_clientserver_description_client_presentation has constant value "0.0" Constant
tech_tf_clientserver_description_client_presentation_processing has constant value "0.0" Constant
tech_tf_clientserver_description_client_server_architecture has constant value "0.0" Constant
tech_tf_clientserver_description_client_server_architecture_p2p has constant value "0.0" Constant
tech_tf_clientserver_description_server_processing has constant value "0.0" Constant
tech_tf_clientserver_description_stand_alone has constant value "0.0" Constant
tech_tf_clientserver_description_web has constant value "0.0" Constant
external_eef_data_quality_rating_c_lang has constant value "False" Constant
project_prf_development_type_other has constant value "False" Constant
project_prf_development_type_poc has constant value "False" Constant
project_prf_development_type_porting has constant value "False" Constant
tech_tf_development_platform_mr has constant value "False" Constant
tech_tf_development_platform_proprietary has constant value "False" Constant
tech_tf_language_type_2gl has constant value "False" Constant
tech_tf_language_type_5gl has constant value "False" Constant
tech_tf_language_type_apg has constant value "False" Constant
project_prf_relative_size_l has constant value "False" Constant
project_prf_relative_size_nan has constant value "False" Constant
project_prf_relative_size_xl has constant value "False" Constant
project_prf_relative_size_xxl has constant value "False" Constant
project_prf_relative_size_xxs has constant value "False" Constant
project_prf_case_tool_used_don_t_know has constant value "False" Constant
project_prf_case_tool_used_no has constant value "False" Constant
project_prf_case_tool_used_yes has constant value "False" Constant
tech_tf_architecture_multi_tier_with_web_interface has constant value "False" Constant
tech_tf_architecture_multi_tier_with_web_public_interface has constant value "False" Constant
tech_tf_architecture_stand_alone has constant value "False" Constant
tech_tf_client_server_don_t_know has constant value "False" Constant
tech_tf_client_server_no has constant value "False" Constant
tech_tf_type_of_server_back_end has constant value "False" Constant
tech_tf_type_of_server_lan_based has constant value "False" Constant
tech_tf_type_of_server_mainframe has constant value "False" Constant
tech_tf_type_of_server_multi_tier_with_web_public_interface has constant value "False" Constant
tech_tf_type_of_server_standalone has constant value "False" Constant
tech_tf_type_of_server_unix has constant value "False" Constant
tech_tf_type_of_server_webserver has constant value "False" Constant
tech_tf_dbms_used_no has constant value "False" Constant
people_prf_project_user_involvement_best has constant value "False" Constant
people_prf_project_user_involvement_don_t_know has constant value "False" Constant
people_prf_project_user_involvement_low has constant value "False" Constant
people_prf_project_user_involvement_nan has constant value "True" Constant
people_prf_project_user_involvement_no has constant value "False" Constant
people_prf_project_user_involvement_yes has constant value "False" Constant
project_prf_currency_multiple_yes_1_000 has constant value "False" Constant
project_prf_currency_multiple_yes_10_000 has constant value "False" Constant
external_eef_organisation_type_top_communications has constant value "0" Constant
external_eef_organisation_type_top_computers & software has constant value "0" Constant
external_eef_organisation_type_top_defence has constant value "0" Constant
external_eef_organisation_type_top_public administration has constant value "0" Constant
external_eef_organisation_type_top_aerospace / automotive has constant value "0" Constant
external_eef_organisation_type_top_transport & storage has constant value "0" Constant
external_eef_organisation_type_top_financial, property & business services has constant value "0" Constant
external_eef_organisation_type_top_education institution has constant value "0" Constant
external_eef_organisation_type_top_community services has constant value "0" Constant
external_eef_organisation_type_top_electricity, gas, water has constant value "0" Constant
external_eef_organisation_type_top_wholesale & retail trade has constant value "0" Constant
external_eef_organisation_type_top_telecommunication has constant value "0" Constant
external_eef_organisation_type_other has constant value "0" Constant
project_prf_application_type_top_unknown has constant value "0" Constant
project_prf_application_type_top_relatively complex application has constant value "0" Constant
project_prf_application_type_top_workflow support & management has constant value "0" Constant
project_prf_application_type_top_business application has constant value "0" Constant
project_prf_application_type_top_embedded system/real_time application has constant value "0" Constant
project_prf_application_type_top_online. esales has constant value "0" Constant
project_prf_application_type_top_management of licences and permits has constant value "0.0" Constant
project_prf_application_type_top_online analysis and reporting has constant value "0" Constant
project_prf_application_type_top_catalogue/register of things or events has constant value "0" Constant
project_prf_application_type_top_software for machine control has constant value "0.0" Constant
project_prf_application_type_top_document management has constant value "0" Constant
project_prf_application_type_top_electronic data interchange has constant value "0" Constant
project_prf_application_type_top_management information system has constant value "0" Constant
project_prf_application_type_top_data warehouse system has constant value "0.0" Constant
project_prf_application_type_top_stock control & order processing has constant value "0" Constant
project_prf_application_type_top_management or performance reporting has constant value "0.0" Constant
external_eef_data_quality_rating_a is highly imbalanced (99.4%) Imbalance
external_eef_data_quality_rating_b is highly imbalanced (95.4%) Imbalance
external_eef_data_quality_rating_d is highly imbalanced (99.3%) Imbalance
project_prf_development_type_enhancement is highly imbalanced (92.3%) Imbalance
project_prf_development_type_new_development is highly imbalanced (92.3%) Imbalance
project_prf_development_type_re_development is highly imbalanced (98.9%) Imbalance
tech_tf_development_platform_mf is highly imbalanced (58.5%) Imbalance
tech_tf_development_platform_nan is highly imbalanced (59.5%) Imbalance
tech_tf_development_platform_pc is highly imbalanced (90.9%) Imbalance
tech_tf_language_type_4gl is highly imbalanced (91.0%) Imbalance
tech_tf_language_type_nan is highly imbalanced (90.8%) Imbalance
project_prf_relative_size_m1 is highly imbalanced (64.1%) Imbalance
project_prf_relative_size_m2 is highly imbalanced (88.1%) Imbalance
project_prf_relative_size_xs is highly imbalanced (96.7%) Imbalance
project_prf_case_tool_used_nan is highly imbalanced (98.7%) Imbalance
process_pmf_prototyping_used_nan is highly imbalanced (78.4%) Imbalance
process_pmf_prototyping_used_yes is highly imbalanced (89.1%) Imbalance
tech_tf_architecture_client_server is highly imbalanced (96.7%) Imbalance
tech_tf_architecture_multi_tier is highly imbalanced (99.5%) Imbalance
tech_tf_architecture_standalone is highly imbalanced (99.5%) Imbalance
tech_tf_client_server_nan is highly imbalanced (77.3%) Imbalance
tech_tf_client_server_yes is highly imbalanced (83.0%) Imbalance
tech_tf_type_of_server_client_server is highly imbalanced (99.9%) Imbalance
tech_tf_type_of_server_nan is highly imbalanced (97.8%) Imbalance
tech_tf_web_development_nan is highly imbalanced (71.8%) Imbalance
tech_tf_web_development_web is highly imbalanced (94.1%) Imbalance
project_prf_currency_multiple_nan is highly imbalanced (51.0%) Imbalance
project_prf_currency_multiple_no is highly imbalanced (96.0%) Imbalance
tech_tf_clientserver_description has 10000 (100.0%) missing values Missing
project_prf_development_type_not_defined has 10000 (100.0%) missing values Missing
tech_tf_development_platform_hand_held has 10000 (100.0%) missing values Missing
project_prf_relative_size_xxxl has 10000 (100.0%) missing values Missing
tech_tf_architecture_multi_tier_client_server has 10000 (100.0%) missing values Missing
tech_tf_client_server_not_applicable has 10000 (100.0%) missing values Missing
tech_tf_type_of_server_proprietary_midrange has 10000 (100.0%) missing values Missing
project_prf_application_type_top_transaction/production system has 10000 (100.0%) missing values Missing
project_prf_application_type_top_financial application area has 10000 (100.0%) missing values Missing
project_prf_application_type_top_client-server has 10000 (100.0%) missing values Missing
project_prf_application_type_top_customer billing/relationship management has 10000 (100.0%) missing values Missing
project_prf_application_group_mathematically_intensive_application is highly skewed (γ1 = 100) Skewed
tech_tf_clientserver_description_nan is highly skewed (γ1 = -70.69653245) Skewed
external_eef_organisation_type_top_manufacturing is highly skewed (γ1 = 28.81984909) Skewed
external_eef_organisation_type_top_telecommunications is highly skewed (γ1 = 30.10587834) Skewed
external_eef_organisation_type_top_government is highly skewed (γ1 = 57.71770092) Skewed
external_eef_organisation_type_top_nan is highly skewed (γ1 = 100) Skewed
external_eef_organisation_type_top_banking is highly skewed (γ1 = 57.71770092) Skewed
external_eef_organisation_type_top_logistics is highly skewed (γ1 = 49.97749193) Skewed
project_prf_application_type_top_financial transaction process/accounting is highly skewed (γ1 = 100) Skewed
project_prf_application_type_top_not recorded is highly skewed (γ1 = 100) Skewed
project_prf_application_type_top_nan is highly skewed (γ1 = 40.7941969) Skewed
project_prf_application_type_top_customer relationship management is highly skewed (γ1 = 100) Skewed
tech_tf_clientserver_description is an unsupported type, check if it needs cleaning or further analysis Unsupported
project_prf_development_type_not_defined is an unsupported type, check if it needs cleaning or further analysis Unsupported
tech_tf_development_platform_hand_held is an unsupported type, check if it needs cleaning or further analysis Unsupported
project_prf_relative_size_xxxl is an unsupported type, check if it needs cleaning or further analysis Unsupported
tech_tf_architecture_multi_tier_client_server is an unsupported type, check if it needs cleaning or further analysis Unsupported
tech_tf_client_server_not_applicable is an unsupported type, check if it needs cleaning or further analysis Unsupported
tech_tf_type_of_server_proprietary_midrange is an unsupported type, check if it needs cleaning or further analysis Unsupported
project_prf_application_type_top_transaction/production system is an unsupported type, check if it needs cleaning or further analysis Unsupported
project_prf_application_type_top_financial application area is an unsupported type, check if it needs cleaning or further analysis Unsupported
project_prf_application_type_top_client-server is an unsupported type, check if it needs cleaning or further analysis Unsupported
project_prf_application_type_top_customer billing/relationship management is an unsupported type, check if it needs cleaning or further analysis Unsupported
process_pmf_docs has 677 (6.8%) zeros Zeros
tech_tf_tools_used has 9137 (91.4%) zeros Zeros
project_prf_application_group_business_application has 2069 (20.7%) zeros Zeros
project_prf_application_group_infrastructure_software has 10000 (100.0%) zeros Zeros
project_prf_application_group_mathematically_intensive_application has 9999 (> 99.9%) zeros Zeros
project_prf_application_group_nan has 9912 (99.1%) zeros Zeros
project_prf_application_group_real_time_application has 10000 (100.0%) zeros Zeros
tech_tf_clientserver_description_browser_server_architecture has 10000 (100.0%) zeros Zeros
tech_tf_clientserver_description_client_server has 9997 (> 99.9%) zeros Zeros
tech_tf_clientserver_description_client_presentation has 10000 (100.0%) zeros Zeros
tech_tf_clientserver_description_client_presentation_processing has 10000 (100.0%) zeros Zeros
tech_tf_clientserver_description_client_server_architecture has 10000 (100.0%) zeros Zeros
tech_tf_clientserver_description_client_server_architecture_p2p has 10000 (100.0%) zeros Zeros
tech_tf_clientserver_description_server_processing has 10000 (100.0%) zeros Zeros
tech_tf_clientserver_description_stand_alone has 10000 (100.0%) zeros Zeros
tech_tf_clientserver_description_web has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_insurance has 9940 (99.4%) zeros Zeros
external_eef_organisation_type_top_medical and health care has 9969 (99.7%) zeros Zeros
external_eef_organisation_type_top_manufacturing has 9988 (99.9%) zeros Zeros
external_eef_organisation_type_top_telecommunications has 9989 (99.9%) zeros Zeros
external_eef_organisation_type_top_government has 9997 (> 99.9%) zeros Zeros
external_eef_organisation_type_top_nan has 9999 (> 99.9%) zeros Zeros
external_eef_organisation_type_top_communications has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_banking has 9997 (> 99.9%) zeros Zeros
external_eef_organisation_type_top_computers & software has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_defence has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_public administration has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_aerospace / automotive has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_transport & storage has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_financial, property & business services has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_education institution has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_community services has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_electricity, gas, water has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_logistics has 9996 (> 99.9%) zeros Zeros
external_eef_organisation_type_top_wholesale & retail trade has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_top_telecommunication has 10000 (100.0%) zeros Zeros
external_eef_organisation_type_other has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_financial transaction process/accounting has 9999 (> 99.9%) zeros Zeros
project_prf_application_type_top_not recorded has 9999 (> 99.9%) zeros Zeros
project_prf_application_type_top_nan has 9994 (99.9%) zeros Zeros
project_prf_application_type_top_unknown has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_customer relationship management has 9999 (> 99.9%) zeros Zeros
project_prf_application_type_top_relatively complex application has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_workflow support & management has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_business application has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_embedded system/real_time application has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_online. esales has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_management of licences and permits has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_online analysis and reporting has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_catalogue/register of things or events has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_software for machine control has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_document management has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_electronic data interchange has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_management information system has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_data warehouse system has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_stock control & order processing has 10000 (100.0%) zeros Zeros
project_prf_application_type_top_management or performance reporting has 10000 (100.0%) zeros Zeros
project_prf_application_type_other has 9848 (98.5%) zeros Zeros

Reproduction

Analysis started2025-06-04 14:05:25.344891
Analysis finished2025-06-04 14:05:26.298289
Duration0.95 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

isbsg_project_id
Real number (ℝ)

Distinct7455
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22350.0781
Minimum3462
Maximum32141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:26.446883image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum3462
5-th percentile14067.45
Q119588.75
median22914.5
Q325728
95-th percentile28729.05
Maximum32141
Range28679
Interquartile range (IQR)6139.25

Descriptive statistics

Standard deviation4517.971123
Coefficient of variation (CV)0.2021456526
Kurtosis0.2522966754
Mean22350.0781
Median Absolute Deviation (MAD)3029
Skewness-0.6373185131
Sum223500781
Variance20412063.07
MonotonicityNot monotonic
2025-06-04T15:05:26.640584image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23076 6
 
0.1%
21004 5
 
0.1%
22443 5
 
0.1%
24402 5
 
0.1%
24250 5
 
0.1%
23944 5
 
0.1%
20144 5
 
0.1%
23484 5
 
0.1%
26153 5
 
0.1%
24872 5
 
0.1%
Other values (7445) 9949
99.5%
ValueCountFrequency (%)
3462 1
< 0.1%
3473 1
< 0.1%
3649 1
< 0.1%
3666 1
< 0.1%
3994 1
< 0.1%
ValueCountFrequency (%)
32141 1
< 0.1%
31947 1
< 0.1%
31881 1
< 0.1%
31673 1
< 0.1%
31542 1
< 0.1%
Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2008.395
Minimum1985
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:26.818408image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1985
5-th percentile2002
Q12006
median2009
Q32011
95-th percentile2013
Maximum2015
Range30
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.479739338
Coefficient of variation (CV)0.001732597093
Kurtosis1.612616094
Mean2008.395
Median Absolute Deviation (MAD)2
Skewness-1.059256003
Sum20083950
Variance12.10858586
MonotonicityNot monotonic
2025-06-04T15:05:26.979596image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2010 1356
13.6%
2011 1276
12.8%
2009 1187
11.9%
2012 1074
10.7%
2008 987
9.9%
2007 877
8.8%
2006 653
6.5%
2013 586
5.9%
2005 534
 
5.3%
2004 408
 
4.1%
Other values (18) 1062
10.6%
ValueCountFrequency (%)
1985 1
 
< 0.1%
1987 1
 
< 0.1%
1988 1
 
< 0.1%
1991 3
< 0.1%
1992 2
< 0.1%
ValueCountFrequency (%)
2015 2
 
< 0.1%
2014 153
 
1.5%
2013 586
5.9%
2012 1074
10.7%
2011 1276
12.8%
Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:27.159544image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length23
Median length18
Mean length12.3375
Min length6

Characters and Unicode

Total characters123375
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowcommunication
2nd rowinsurance
3rd rowlogistics
4th rowlogistics
5th rowgovernment
ValueCountFrequency (%)
manufacturing 1396
 
9.7%
1273
 
8.9%
industry 1243
 
8.7%
service 1243
 
8.7%
communication 1213
 
8.5%
banking 661
 
4.6%
government 603
 
4.2%
mining 546
 
3.8%
utilities 533
 
3.7%
electronics 471
 
3.3%
Other values (15) 5148
35.9%
2025-06-04T15:05:27.528984image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 14367
11.6%
n 13856
11.2%
c 9951
 
8.1%
e 9703
 
7.9%
t 8904
 
7.2%
a 8135
 
6.6%
u 7560
 
6.1%
r 7337
 
5.9%
s 7104
 
5.8%
o 6177
 
5.0%
Other values (15) 30281
24.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 123375
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 14367
11.6%
n 13856
11.2%
c 9951
 
8.1%
e 9703
 
7.9%
t 8904
 
7.2%
a 8135
 
6.6%
u 7560
 
6.1%
r 7337
 
5.9%
s 7104
 
5.8%
o 6177
 
5.0%
Other values (15) 30281
24.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 123375
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 14367
11.6%
n 13856
11.2%
c 9951
 
8.1%
e 9703
 
7.9%
t 8904
 
7.2%
a 8135
 
6.6%
u 7560
 
6.1%
r 7337
 
5.9%
s 7104
 
5.8%
o 6177
 
5.0%
Other values (15) 30281
24.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 123375
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 14367
11.6%
n 13856
11.2%
c 9951
 
8.1%
e 9703
 
7.9%
t 8904
 
7.2%
a 8135
 
6.6%
u 7560
 
6.1%
r 7337
 
5.9%
s 7104
 
5.8%
o 6177
 
5.0%
Other values (15) 30281
24.5%
Distinct76
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:27.767123image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length32
Median length26
Mean length7.2198
Min length2

Characters and Unicode

Total characters72198
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowrpg
2nd rowMissing
3rd rowMissing
4th rowinformatica powercenter
5th rowingres
ValueCountFrequency (%)
missing 1719
 
14.8%
dotnet 999
 
8.6%
visual 659
 
5.7%
java 438
 
3.8%
cobol 378
 
3.3%
csp 317
 
2.7%
focus 301
 
2.6%
informatica 274
 
2.4%
powercenter 274
 
2.4%
rally 268
 
2.3%
Other values (79) 5962
51.4%
2025-06-04T15:05:28.171206image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 7114
 
9.9%
i 6824
 
9.5%
a 5603
 
7.8%
e 5477
 
7.6%
o 5085
 
7.0%
n 4943
 
6.8%
l 4281
 
5.9%
t 4024
 
5.6%
r 3621
 
5.0%
c 3268
 
4.5%
Other values (27) 21958
30.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 72198
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 7114
 
9.9%
i 6824
 
9.5%
a 5603
 
7.8%
e 5477
 
7.6%
o 5085
 
7.0%
n 4943
 
6.8%
l 4281
 
5.9%
t 4024
 
5.6%
r 3621
 
5.0%
c 3268
 
4.5%
Other values (27) 21958
30.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 72198
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 7114
 
9.9%
i 6824
 
9.5%
a 5603
 
7.8%
e 5477
 
7.6%
o 5085
 
7.0%
n 4943
 
6.8%
l 4281
 
5.9%
t 4024
 
5.6%
r 3621
 
5.0%
c 3268
 
4.5%
Other values (27) 21958
30.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 72198
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 7114
 
9.9%
i 6824
 
9.5%
a 5603
 
7.8%
e 5477
 
7.6%
o 5085
 
7.0%
n 4943
 
6.8%
l 4281
 
5.9%
t 4024
 
5.6%
r 3621
 
5.0%
c 3268
 
4.5%
Other values (27) 21958
30.4%
Distinct6682
Distinct (%)66.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean719.9928
Minimum-9818
Maximum11166
Zeros0
Zeros (%)0.0%
Negative4094
Negative (%)40.9%
Memory size78.3 KiB
2025-06-04T15:05:28.385695image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum-9818
5-th percentile-4314.05
Q1-1369.25
median723.5
Q32818.25
95-th percentile5627.35
Maximum11166
Range20984
Interquartile range (IQR)4187.5

Descriptive statistics

Standard deviation3033.230382
Coefficient of variation (CV)4.212862103
Kurtosis-0.1706022683
Mean719.9928
Median Absolute Deviation (MAD)2093.5
Skewness-0.02926949077
Sum7199928
Variance9200486.547
MonotonicityNot monotonic
2025-06-04T15:05:28.568038image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2258 6
 
0.1%
991 6
 
0.1%
-165 6
 
0.1%
-256 6
 
0.1%
219 5
 
0.1%
1004 5
 
0.1%
808 5
 
0.1%
2469 5
 
0.1%
1297 5
 
0.1%
238 5
 
0.1%
Other values (6672) 9946
99.5%
ValueCountFrequency (%)
-9818 1
< 0.1%
-9063 1
< 0.1%
-8901 1
< 0.1%
-8773 1
< 0.1%
-8691 1
< 0.1%
ValueCountFrequency (%)
11166 1
< 0.1%
10794 1
< 0.1%
10729 1
< 0.1%
10678 1
< 0.1%
10598 1
< 0.1%
Distinct9581
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-15783.9806
Minimum-115694
Maximum96340
Zeros0
Zeros (%)0.0%
Negative6756
Negative (%)67.6%
Memory size78.3 KiB
2025-06-04T15:05:28.753381image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum-115694
5-th percentile-69871.65
Q1-39803.75
median-16722
Q37394.75
95-th percentile41089.2
Maximum96340
Range212034
Interquartile range (IQR)47198.5

Descriptive statistics

Standard deviation33447.08301
Coefficient of variation (CV)-2.119052466
Kurtosis-0.3460712446
Mean-15783.9806
Median Absolute Deviation (MAD)23614.5
Skewness0.1191773745
Sum-157839806
Variance1118707362
MonotonicityNot monotonic
2025-06-04T15:05:28.935977image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1503 3
 
< 0.1%
-32024 3
 
< 0.1%
5190 3
 
< 0.1%
-13121 3
 
< 0.1%
-48191 3
 
< 0.1%
10740 3
 
< 0.1%
-32057 3
 
< 0.1%
-25776 3
 
< 0.1%
-15703 3
 
< 0.1%
-27439 3
 
< 0.1%
Other values (9571) 9970
99.7%
ValueCountFrequency (%)
-115694 1
< 0.1%
-115230 1
< 0.1%
-115006 1
< 0.1%
-108336 1
< 0.1%
-104474 1
< 0.1%
ValueCountFrequency (%)
96340 1
< 0.1%
93931 1
< 0.1%
90763 1
< 0.1%
89158 1
< 0.1%
85463 1
< 0.1%
Distinct9781
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3225.0239
Minimum-186288
Maximum222614
Zeros0
Zeros (%)0.0%
Negative4819
Negative (%)48.2%
Memory size78.3 KiB
2025-06-04T15:05:29.228815image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum-186288
5-th percentile-99134.85
Q1-40283.25
median2706.5
Q345949.25
95-th percentile105919.9
Maximum222614
Range408902
Interquartile range (IQR)86232.5

Descriptive statistics

Standard deviation61956.9936
Coefficient of variation (CV)19.21132851
Kurtosis-0.2784469736
Mean3225.0239
Median Absolute Deviation (MAD)43120
Skewness0.04493996153
Sum32250239
Variance3838669057
MonotonicityNot monotonic
2025-06-04T15:05:29.440014image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-43293 3
 
< 0.1%
-4331 3
 
< 0.1%
-6897 2
 
< 0.1%
-13627 2
 
< 0.1%
29970 2
 
< 0.1%
72952 2
 
< 0.1%
18896 2
 
< 0.1%
46569 2
 
< 0.1%
-30663 2
 
< 0.1%
-26399 2
 
< 0.1%
Other values (9771) 9978
99.8%
ValueCountFrequency (%)
-186288 1
< 0.1%
-183056 1
< 0.1%
-181373 1
< 0.1%
-175778 1
< 0.1%
-171757 1
< 0.1%
ValueCountFrequency (%)
222614 1
< 0.1%
219983 1
< 0.1%
205023 1
< 0.1%
197911 1
< 0.1%
197533 1
< 0.1%
Distinct9969
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.72467988
Minimum1.8506812
Maximum531.80707
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:29.684195image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1.8506812
5-th percentile18.39736325
Q141.1439425
median69.380365
Q3111.0868925
95-th percentile203.7300875
Maximum531.80707
Range529.9563888
Interquartile range (IQR)69.94295

Descriptive statistics

Standard deviation60.92588447
Coefficient of variation (CV)0.7191043336
Kurtosis4.554442958
Mean84.72467988
Median Absolute Deviation (MAD)33.025847
Skewness1.703781619
Sum847246.7988
Variance3711.963398
MonotonicityNot monotonic
2025-06-04T15:05:29.864719image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110.91622 2
 
< 0.1%
24.500849 2
 
< 0.1%
30.163559 2
 
< 0.1%
127.88832 2
 
< 0.1%
28.75472 2
 
< 0.1%
34.56112 2
 
< 0.1%
57.252583 2
 
< 0.1%
53.18797 2
 
< 0.1%
44.410645 2
 
< 0.1%
82.43003 2
 
< 0.1%
Other values (9959) 9980
99.8%
ValueCountFrequency (%)
1.8506812 1
< 0.1%
3.1457105 1
< 0.1%
3.3294318 1
< 0.1%
3.4460936 1
< 0.1%
3.5797927 1
< 0.1%
ValueCountFrequency (%)
531.80707 1
< 0.1%
528.92725 1
< 0.1%
501.90027 1
< 0.1%
499.3703 1
< 0.1%
497.7598 1
< 0.1%
Distinct9965
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.80047364
Minimum0.9849506
Maximum421.3706
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:30.059340image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.9849506
5-th percentile8.0782815
Q122.7014045
median43.5275385
Q377.8057775
95-th percentile161.559128
Maximum421.3706
Range420.3856494
Interquartile range (IQR)55.104373

Descriptive statistics

Standard deviation52.53445318
Coefficient of variation (CV)0.8934358846
Kurtosis5.971149454
Mean58.80047364
Median Absolute Deviation (MAD)24.67106
Skewness2.05804437
Sum588004.7364
Variance2759.868771
MonotonicityNot monotonic
2025-06-04T15:05:30.239528image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.402885 2
 
< 0.1%
23.917707 2
 
< 0.1%
6.877123 2
 
< 0.1%
17.264214 2
 
< 0.1%
19.25552 2
 
< 0.1%
8.848203 2
 
< 0.1%
4.038886 2
 
< 0.1%
44.727898 2
 
< 0.1%
77.80477 2
 
< 0.1%
89.9506 2
 
< 0.1%
Other values (9955) 9980
99.8%
ValueCountFrequency (%)
0.9849506 1
< 0.1%
1.0384135 1
< 0.1%
1.3483645 1
< 0.1%
1.3551627 1
< 0.1%
1.3717808 1
< 0.1%
ValueCountFrequency (%)
421.3706 1
< 0.1%
395.35 1
< 0.1%
393.2508 1
< 0.1%
389.28998 1
< 0.1%
384.655 1
< 0.1%
Distinct9927
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.82536534
Minimum0.11597838
Maximum301.03598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:30.426431image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.11597838
5-th percentile3.16574715
Q19.147216
median18.3224305
Q333.63572525
95-th percentile74.208757
Maximum301.03598
Range300.9200016
Interquartile range (IQR)24.48850925

Descriptive statistics

Standard deviation25.20479974
Coefficient of variation (CV)0.9759706942
Kurtosis11.86343461
Mean25.82536534
Median Absolute Deviation (MAD)10.87361585
Skewness2.606890516
Sum258253.6534
Variance635.2819301
MonotonicityNot monotonic
2025-06-04T15:05:30.634657image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.35999 2
 
< 0.1%
9.098196 2
 
< 0.1%
13.3162985 2
 
< 0.1%
4.699246 2
 
< 0.1%
26.128439 2
 
< 0.1%
7.238941 2
 
< 0.1%
2.1479144 2
 
< 0.1%
21.828688 2
 
< 0.1%
2.8070111 2
 
< 0.1%
18.199156 2
 
< 0.1%
Other values (9917) 9980
99.8%
ValueCountFrequency (%)
0.11597838 1
< 0.1%
0.11707131 1
< 0.1%
0.20887682 1
< 0.1%
0.21999891 1
< 0.1%
0.23009238 1
< 0.1%
ValueCountFrequency (%)
301.03598 1
< 0.1%
298.33914 1
< 0.1%
298.03873 1
< 0.1%
285.46826 1
< 0.1%
225.88918 1
< 0.1%
Distinct9994
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.16512779
Minimum0.81893563
Maximum45.248234
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:30.862152image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.81893563
5-th percentile3.73878554
Q17.278216
median10.8775435
Q315.79516575
95-th percentile24.93598825
Maximum45.248234
Range44.42929837
Interquartile range (IQR)8.51694975

Descriptive statistics

Standard deviation6.591051834
Coefficient of variation (CV)0.5417988159
Kurtosis1.09320122
Mean12.16512779
Median Absolute Deviation (MAD)4.069735
Skewness1.001189139
Sum121651.2779
Variance43.44196427
MonotonicityNot monotonic
2025-06-04T15:05:31.073267image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.576813 2
 
< 0.1%
7.1710677 2
 
< 0.1%
9.288972 2
 
< 0.1%
13.552267 2
 
< 0.1%
7.264723 2
 
< 0.1%
6.466133 2
 
< 0.1%
22.12607 1
 
< 0.1%
9.172197 1
 
< 0.1%
13.598373 1
 
< 0.1%
3.3072953 1
 
< 0.1%
Other values (9984) 9984
99.8%
ValueCountFrequency (%)
0.81893563 1
< 0.1%
1.0410031 1
< 0.1%
1.1151844 1
< 0.1%
1.1920378 1
< 0.1%
1.200994 1
< 0.1%
ValueCountFrequency (%)
45.248234 1
< 0.1%
44.804585 1
< 0.1%
44.52815 1
< 0.1%
41.897877 1
< 0.1%
41.824856 1
< 0.1%
Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:31.234854image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.6818
Min length1

Characters and Unicode

Total characters66818
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMissing
2nd rowMissing
3rd rowMissing
4th rowMissing
5th rowMissing
ValueCountFrequency (%)
missing 8885
88.8%
5_8 243
 
2.4%
9_14 198
 
2.0%
91_100 172
 
1.7%
41_50 89
 
0.9%
31_40 64
 
0.6%
15_20 63
 
0.6%
3_4 55
 
0.5%
21_30 44
 
0.4%
2 41
 
0.4%
Other values (6) 146
 
1.5%
2025-06-04T15:05:31.541066image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 17770
26.6%
i 17770
26.6%
M 8885
13.3%
n 8885
13.3%
g 8885
13.3%
_ 1010
 
1.5%
1 978
 
1.5%
0 716
 
1.1%
4 406
 
0.6%
5 406
 
0.6%
Other values (7) 1107
 
1.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 66818
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 17770
26.6%
i 17770
26.6%
M 8885
13.3%
n 8885
13.3%
g 8885
13.3%
_ 1010
 
1.5%
1 978
 
1.5%
0 716
 
1.1%
4 406
 
0.6%
5 406
 
0.6%
Other values (7) 1107
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 66818
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 17770
26.6%
i 17770
26.6%
M 8885
13.3%
n 8885
13.3%
g 8885
13.3%
_ 1010
 
1.5%
1 978
 
1.5%
0 716
 
1.1%
4 406
 
0.6%
5 406
 
0.6%
Other values (7) 1107
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 66818
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 17770
26.6%
i 17770
26.6%
M 8885
13.3%
n 8885
13.3%
g 8885
13.3%
_ 1010
 
1.5%
1 978
 
1.5%
0 716
 
1.1%
4 406
 
0.6%
5 406
 
0.6%
Other values (7) 1107
 
1.7%

project_prf_max_team_size
Real number (ℝ)

Distinct362
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.0128
Minimum-191
Maximum224
Zeros50
Zeros (%)0.5%
Negative3028
Negative (%)30.3%
Memory size78.3 KiB
2025-06-04T15:05:31.728732image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum-191
5-th percentile-75
Q1-11
median34
Q379.25
95-th percentile136
Maximum224
Range415
Interquartile range (IQR)90.25

Descriptive statistics

Standard deviation64.13764573
Coefficient of variation (CV)1.942811447
Kurtosis-0.3395325534
Mean33.0128
Median Absolute Deviation (MAD)45
Skewness-0.1095570956
Sum330128
Variance4113.6376
MonotonicityNot monotonic
2025-06-04T15:05:31.915789image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
53 76
 
0.8%
27 73
 
0.7%
43 70
 
0.7%
13 68
 
0.7%
15 68
 
0.7%
28 67
 
0.7%
42 66
 
0.7%
18 66
 
0.7%
12 66
 
0.7%
35 66
 
0.7%
Other values (352) 9314
93.1%
ValueCountFrequency (%)
-191 1
< 0.1%
-181 1
< 0.1%
-169 1
< 0.1%
-165 2
< 0.1%
-161 1
< 0.1%
ValueCountFrequency (%)
224 1
< 0.1%
221 1
< 0.1%
212 1
< 0.1%
209 1
< 0.1%
206 1
< 0.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:32.107651image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters170000
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowagile development
2nd rowagile development
3rd rowagile development
4th rowagile development
5th rowagile development
ValueCountFrequency (%)
agile 10000
50.0%
development 10000
50.0%
2025-06-04T15:05:32.429955image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 40000
23.5%
l 20000
11.8%
a 10000
 
5.9%
g 10000
 
5.9%
i 10000
 
5.9%
10000
 
5.9%
d 10000
 
5.9%
v 10000
 
5.9%
o 10000
 
5.9%
p 10000
 
5.9%
Other values (3) 30000
17.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 170000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 40000
23.5%
l 20000
11.8%
a 10000
 
5.9%
g 10000
 
5.9%
i 10000
 
5.9%
10000
 
5.9%
d 10000
 
5.9%
v 10000
 
5.9%
o 10000
 
5.9%
p 10000
 
5.9%
Other values (3) 30000
17.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 170000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 40000
23.5%
l 20000
11.8%
a 10000
 
5.9%
g 10000
 
5.9%
i 10000
 
5.9%
10000
 
5.9%
d 10000
 
5.9%
v 10000
 
5.9%
o 10000
 
5.9%
p 10000
 
5.9%
Other values (3) 30000
17.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 170000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 40000
23.5%
l 20000
11.8%
a 10000
 
5.9%
g 10000
 
5.9%
i 10000
 
5.9%
10000
 
5.9%
d 10000
 
5.9%
v 10000
 
5.9%
o 10000
 
5.9%
p 10000
 
5.9%
Other values (3) 30000
17.6%

process_pmf_docs
Real number (ℝ)

Zeros 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1121
Minimum-11
Maximum15
Zeros677
Zeros (%)6.8%
Negative1930
Negative (%)19.3%
Memory size78.3 KiB
2025-06-04T15:05:32.628698image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum-11
5-th percentile-4
Q10
median3
Q36
95-th percentile10
Maximum15
Range26
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.112107067
Coefficient of variation (CV)1.321328706
Kurtosis-0.225642284
Mean3.1121
Median Absolute Deviation (MAD)3
Skewness-0.1486808658
Sum31121
Variance16.90942453
MonotonicityNot monotonic
2025-06-04T15:05:32.827842image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
4 1005
10.1%
2 924
9.2%
3 882
 
8.8%
5 882
 
8.8%
1 805
 
8.1%
6 753
 
7.5%
7 689
 
6.9%
0 677
 
6.8%
-1 571
 
5.7%
8 526
 
5.3%
Other values (17) 2286
22.9%
ValueCountFrequency (%)
-11 2
 
< 0.1%
-10 5
 
0.1%
-9 13
 
0.1%
-8 36
0.4%
-7 50
0.5%
ValueCountFrequency (%)
15 1
 
< 0.1%
14 15
 
0.1%
13 42
 
0.4%
12 87
0.9%
11 164
1.6%
Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:33.002534image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length161
Median length7
Mean length7.2095
Min length7

Characters and Unicode

Total characters72095
Distinct characters30
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)0.1%

Sample

1st rowMissing
2nd rowMissing
3rd rowMissing
4th rowMissing
5th rowMissing
ValueCountFrequency (%)
missing 9976
97.1%
data 32
 
0.3%
31
 
0.3%
interface 22
 
0.2%
retrieval 17
 
0.2%
presentation 17
 
0.2%
run 16
 
0.2%
a 16
 
0.2%
computer_human 16
 
0.2%
web/html 15
 
0.1%
Other values (23) 118
 
1.1%
2025-06-04T15:05:33.389846image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 20083
27.9%
s 20043
27.8%
n 10120
14.0%
g 9995
13.9%
M 9976
13.8%
276
 
0.4%
e 230
 
0.3%
a 198
 
0.3%
r 192
 
0.3%
t 181
 
0.3%
Other values (20) 801
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 72095
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 20083
27.9%
s 20043
27.8%
n 10120
14.0%
g 9995
13.9%
M 9976
13.8%
276
 
0.4%
e 230
 
0.3%
a 198
 
0.3%
r 192
 
0.3%
t 181
 
0.3%
Other values (20) 801
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 72095
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 20083
27.9%
s 20043
27.8%
n 10120
14.0%
g 9995
13.9%
M 9976
13.8%
276
 
0.4%
e 230
 
0.3%
a 198
 
0.3%
r 192
 
0.3%
t 181
 
0.3%
Other values (20) 801
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 72095
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 20083
27.9%
s 20043
27.8%
n 10120
14.0%
g 9995
13.9%
M 9976
13.8%
276
 
0.4%
e 230
 
0.3%
a 198
 
0.3%
r 192
 
0.3%
t 181
 
0.3%
Other values (20) 801
 
1.1%
Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:33.554242image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length104
Median length7
Mean length7.0862
Min length7

Characters and Unicode

Total characters70862
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowMissing
2nd rowMissing
3rd rowMissing
4th rowMissing
5th rowMissing
ValueCountFrequency (%)
missing 9988
99.0%
server 41
 
0.4%
database 11
 
0.1%
html/web 11
 
0.1%
file/print 5
 
< 0.1%
messaging 5
 
< 0.1%
security/authentication 5
 
< 0.1%
multi_user 4
 
< 0.1%
legacy 4
 
< 0.1%
application 4
 
< 0.1%
Other values (5) 12
 
0.1%
2025-06-04T15:05:33.903850image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 20047
28.3%
i 20021
28.3%
n 10018
14.1%
g 10002
14.1%
M 9988
14.1%
e 140
 
0.2%
r 99
 
0.1%
90
 
0.1%
t 64
 
0.1%
a 63
 
0.1%
Other values (17) 330
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 70862
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 20047
28.3%
i 20021
28.3%
n 10018
14.1%
g 10002
14.1%
M 9988
14.1%
e 140
 
0.2%
r 99
 
0.1%
90
 
0.1%
t 64
 
0.1%
a 63
 
0.1%
Other values (17) 330
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 70862
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 20047
28.3%
i 20021
28.3%
n 10018
14.1%
g 10002
14.1%
M 9988
14.1%
e 140
 
0.2%
r 99
 
0.1%
90
 
0.1%
t 64
 
0.1%
a 63
 
0.1%
Other values (17) 330
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 70862
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 20047
28.3%
i 20021
28.3%
n 10018
14.1%
g 10002
14.1%
M 9988
14.1%
e 140
 
0.2%
r 99
 
0.1%
90
 
0.1%
t 64
 
0.1%
a 63
 
0.1%
Other values (17) 330
 
0.5%

tech_tf_tools_used
Real number (ℝ)

Zeros 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4927
Minimum0
Maximum10
Zeros9137
Zeros (%)91.4%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:34.228232image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.831688352
Coefficient of variation (CV)3.717654459
Kurtosis15.36266249
Mean0.4927
Median Absolute Deviation (MAD)0
Skewness4.006634252
Sum4927
Variance3.355082218
MonotonicityNot monotonic
2025-06-04T15:05:34.373604image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 9137
91.4%
9 227
 
2.3%
2 167
 
1.7%
4 164
 
1.6%
10 84
 
0.8%
5 63
 
0.6%
6 55
 
0.5%
3 42
 
0.4%
1 27
 
0.3%
8 18
 
0.2%
ValueCountFrequency (%)
0 9137
91.4%
1 27
 
0.3%
2 167
 
1.7%
3 42
 
0.4%
4 164
 
1.6%
ValueCountFrequency (%)
10 84
 
0.8%
9 227
2.3%
8 18
 
0.2%
7 16
 
0.2%
6 55
 
0.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7931
Minimum0
Maximum1
Zeros2069
Zeros (%)20.7%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:34.513852image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4051034447
Coefficient of variation (CV)0.5107848249
Kurtosis0.09477514735
Mean0.7931
Median Absolute Deviation (MAD)0
Skewness-1.447327272
Sum7931
Variance0.1641088009
MonotonicityNot monotonic
2025-06-04T15:05:34.644176image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 7931
79.3%
0 2069
 
20.7%
ValueCountFrequency (%)
0 2069
 
20.7%
1 7931
79.3%
ValueCountFrequency (%)
1 7931
79.3%
0 2069
 
20.7%

project_prf_application_group_infrastructure_software
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:34.774710image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:34.901725image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0001
Minimum0
Maximum1
Zeros9999
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:35.036845image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01
Coefficient of variation (CV)100
Kurtosis10000
Mean0.0001
Median Absolute Deviation (MAD)0
Skewness100
Sum1
Variance0.0001
MonotonicityNot monotonic
2025-06-04T15:05:35.170286image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
0 9999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 9999
> 99.9%

project_prf_application_group_nan
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0088
Minimum0
Maximum1
Zeros9912
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:35.305113image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09339931661
Coefficient of variation (CV)10.61355871
Kurtosis108.7001842
Mean0.0088
Median Absolute Deviation (MAD)0
Skewness10.52038232
Sum88
Variance0.008723432343
MonotonicityNot monotonic
2025-06-04T15:05:35.439844image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9912
99.1%
1 88
 
0.9%
ValueCountFrequency (%)
0 9912
99.1%
1 88
 
0.9%
ValueCountFrequency (%)
1 88
 
0.9%
0 9912
99.1%

project_prf_application_group_real_time_application
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:35.566211image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:35.683432image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:35.811688image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:35.921008image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

tech_tf_clientserver_description_client_server
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing3
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros9997
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:36.057643image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:36.173772image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 9997
> 99.9%
(Missing) 3
 
< 0.1%
ValueCountFrequency (%)
0 9997
> 99.9%
ValueCountFrequency (%)
0 9997
> 99.9%

tech_tf_clientserver_description_client_presentation
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:36.302604image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:36.425584image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:36.557729image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:36.688155image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:36.817467image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:36.945726image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:37.068013image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:37.198295image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

tech_tf_clientserver_description_nan
Real number (ℝ)

Skewed 

Distinct2
Distinct (%)< 0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.99979998
Minimum0
Maximum1
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:37.322127image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01414213548
Coefficient of variation (CV)0.01414496476
Kurtosis4996.9992
Mean0.99979998
Median Absolute Deviation (MAD)0
Skewness-70.69653245
Sum9997
Variance0.000199999996
MonotonicityNot monotonic
2025-06-04T15:05:37.458645image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 9997
> 99.9%
0 2
 
< 0.1%
(Missing) 1
 
< 0.1%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 9997
> 99.9%
ValueCountFrequency (%)
1 9997
> 99.9%
0 2
 
< 0.1%

tech_tf_clientserver_description_server_processing
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:37.586301image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:37.726027image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

tech_tf_clientserver_description_stand_alone
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:37.851919image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:37.980065image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

tech_tf_clientserver_description_web
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:38.106574image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:38.235995image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9995 
True
 
5
ValueCountFrequency (%)
False 9995
> 99.9%
True 5
 
0.1%
2025-06-04T15:05:38.366641image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
9949 
False
 
51
ValueCountFrequency (%)
True 9949
99.5%
False 51
 
0.5%
2025-06-04T15:05:38.477130image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:38.589504image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9994 
True
 
6
ValueCountFrequency (%)
False 9994
99.9%
True 6
 
0.1%
2025-06-04T15:05:38.688144image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
9905 
False
 
95
ValueCountFrequency (%)
True 9905
99.1%
False 95
 
0.9%
2025-06-04T15:05:38.799273image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9906 
True
 
94
ValueCountFrequency (%)
False 9906
99.1%
True 94
 
0.9%
2025-06-04T15:05:38.905317image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:39.005775image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:39.101758image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:39.197292image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9990 
True
 
10
ValueCountFrequency (%)
False 9990
99.9%
True 10
 
0.1%
2025-06-04T15:05:39.291009image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9164 
True
 
836
ValueCountFrequency (%)
False 9164
91.6%
True 836
 
8.4%
2025-06-04T15:05:39.402060image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:39.505659image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
7524 
True
2476 
ValueCountFrequency (%)
False 7524
75.2%
True 2476
 
24.8%
2025-06-04T15:05:39.609831image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9193 
True
 
807
ValueCountFrequency (%)
False 9193
91.9%
True 807
 
8.1%
2025-06-04T15:05:39.724889image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9885 
True
 
115
ValueCountFrequency (%)
False 9885
98.9%
True 115
 
1.1%
2025-06-04T15:05:39.830363image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:40.112849image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_language_type_2gl
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:40.208436image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
6672 
False
3328 
ValueCountFrequency (%)
True 6672
66.7%
False 3328
33.3%
2025-06-04T15:05:40.308344image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_language_type_4gl
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9886 
True
 
114
ValueCountFrequency (%)
False 9886
98.9%
True 114
 
1.1%
2025-06-04T15:05:40.417116image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_language_type_5gl
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:40.512186image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_language_type_apg
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:40.629775image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_language_type_nan
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9883 
True
 
117
ValueCountFrequency (%)
False 9883
98.8%
True 117
 
1.2%
2025-06-04T15:05:40.730848image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

project_prf_relative_size_l
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:40.822845image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

project_prf_relative_size_m1
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9318 
True
 
682
ValueCountFrequency (%)
False 9318
93.2%
True 682
 
6.8%
2025-06-04T15:05:40.933378image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

project_prf_relative_size_m2
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9839 
True
 
161
ValueCountFrequency (%)
False 9839
98.4%
True 161
 
1.6%
2025-06-04T15:05:41.029042image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:41.140520image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
8542 
True
1458 
ValueCountFrequency (%)
False 8542
85.4%
True 1458
 
14.6%
2025-06-04T15:05:41.241886image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:41.337997image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

project_prf_relative_size_xs
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9966 
True
 
34
ValueCountFrequency (%)
False 9966
99.7%
True 34
 
0.3%
2025-06-04T15:05:41.443655image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:41.544648image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:41.638717image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:41.733430image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
9988 
False
 
12
ValueCountFrequency (%)
True 9988
99.9%
False 12
 
0.1%
2025-06-04T15:05:41.828351image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:41.932962image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:42.017710image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
9657 
False
 
343
ValueCountFrequency (%)
True 9657
96.6%
False 343
 
3.4%
2025-06-04T15:05:42.126151image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9855 
True
 
145
ValueCountFrequency (%)
False 9855
98.6%
True 145
 
1.5%
2025-06-04T15:05:42.228477image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9966 
True
 
34
ValueCountFrequency (%)
False 9966
99.7%
True 34
 
0.3%
2025-06-04T15:05:42.333659image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9996 
True
 
4
ValueCountFrequency (%)
False 9996
> 99.9%
True 4
 
< 0.1%
2025-06-04T15:05:42.434368image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:42.539268image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:42.639903image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
6818 
True
3182 
ValueCountFrequency (%)
False 6818
68.2%
True 3182
31.8%
2025-06-04T15:05:42.745425image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:42.853256image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9996 
True
 
4
ValueCountFrequency (%)
False 9996
> 99.9%
True 4
 
< 0.1%
2025-06-04T15:05:42.950827image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:43.051735image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_client_server_nan
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
9633 
False
 
367
ValueCountFrequency (%)
True 9633
96.3%
False 367
 
3.7%
2025-06-04T15:05:43.138152image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_client_server_no
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:43.252680image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_client_server_yes
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9748 
True
 
252
ValueCountFrequency (%)
False 9748
97.5%
True 252
 
2.5%
2025-06-04T15:05:43.353081image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:43.451073image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9999 
True
 
1
ValueCountFrequency (%)
False 9999
> 99.9%
True 1
 
< 0.1%
2025-06-04T15:05:43.551677image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:43.651404image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:43.745716image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:43.826783image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_type_of_server_nan
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
9979 
False
 
21
ValueCountFrequency (%)
True 9979
99.8%
False 21
 
0.2%
2025-06-04T15:05:43.941410image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:44.039938image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_type_of_server_unix
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:44.134563image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:44.228492image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_web_development_nan
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
9510 
False
 
490
ValueCountFrequency (%)
True 9510
95.1%
False 490
 
4.9%
2025-06-04T15:05:44.333067image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_web_development_web
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9932 
True
 
68
ValueCountFrequency (%)
False 9932
99.3%
True 68
 
0.7%
2025-06-04T15:05:44.433798image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
8387 
False
1613 
ValueCountFrequency (%)
True 8387
83.9%
False 1613
 
16.1%
2025-06-04T15:05:44.540926image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_dbms_used_no
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:44.654836image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
7749 
True
2251 
ValueCountFrequency (%)
False 7749
77.5%
True 2251
 
22.5%
2025-06-04T15:05:44.757950image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:44.855050image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:44.959857image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:45.056793image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
10000 
ValueCountFrequency (%)
True 10000
100.0%
2025-06-04T15:05:45.150228image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:45.250822image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:45.337834image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
8933 
False
1067 
ValueCountFrequency (%)
True 8933
89.3%
False 1067
 
10.7%
2025-06-04T15:05:45.446806image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9957 
True
 
43
ValueCountFrequency (%)
False 9957
99.6%
True 43
 
0.4%
2025-06-04T15:05:45.554399image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:45.653326image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-04T15:05:45.748734image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.006
Minimum0
Maximum1
Zeros9940
Zeros (%)99.4%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:45.859403image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07723079994
Coefficient of variation (CV)12.87179999
Kurtosis161.7541686
Mean0.006
Median Absolute Deviation (MAD)0
Skewness12.79538267
Sum60
Variance0.00596459646
MonotonicityNot monotonic
2025-06-04T15:05:45.991681image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9940
99.4%
1 60
 
0.6%
ValueCountFrequency (%)
0 9940
99.4%
1 60
 
0.6%
ValueCountFrequency (%)
1 60
 
0.6%
0 9940
99.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0031
Minimum0
Maximum1
Zeros9969
Zeros (%)99.7%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:46.122041image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05559405607
Coefficient of variation (CV)17.93356647
Kurtosis317.7432041
Mean0.0031
Median Absolute Deviation (MAD)0
Skewness17.87958768
Sum31
Variance0.00309069907
MonotonicityNot monotonic
2025-06-04T15:05:46.469493image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9969
99.7%
1 31
 
0.3%
ValueCountFrequency (%)
0 9969
99.7%
1 31
 
0.3%
ValueCountFrequency (%)
1 31
 
0.3%
0 9969
99.7%

external_eef_organisation_type_top_manufacturing
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0012
Minimum0
Maximum1
Zeros9988
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:46.607894image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.03462195644
Coefficient of variation (CV)28.85163037
Kurtosis828.7494514
Mean0.0012
Median Absolute Deviation (MAD)0
Skewness28.81984909
Sum12
Variance0.001198679868
MonotonicityNot monotonic
2025-06-04T15:05:46.790748image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9988
99.9%
1 12
 
0.1%
ValueCountFrequency (%)
0 9988
99.9%
1 12
 
0.1%
ValueCountFrequency (%)
1 12
 
0.1%
0 9988
99.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0011
Minimum0
Maximum1
Zeros9989
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:46.943398image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.03314965897
Coefficient of variation (CV)30.13605361
Kurtosis904.5448193
Mean0.0011
Median Absolute Deviation (MAD)0
Skewness30.10587834
Sum11
Variance0.00109889989
MonotonicityNot monotonic
2025-06-04T15:05:47.090301image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9989
99.9%
1 11
 
0.1%
ValueCountFrequency (%)
0 9989
99.9%
1 11
 
0.1%
ValueCountFrequency (%)
1 11
 
0.1%
0 9989
99.9%

external_eef_organisation_type_top_government
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0003
Minimum0
Maximum1
Zeros9997
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:47.222431image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01731877577
Coefficient of variation (CV)57.72925255
Kurtosis3329.999
Mean0.0003
Median Absolute Deviation (MAD)0
Skewness57.71770092
Sum3
Variance0.000299939994
MonotonicityNot monotonic
2025-06-04T15:05:47.354907image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9997
> 99.9%
1 3
 
< 0.1%
ValueCountFrequency (%)
0 9997
> 99.9%
1 3
 
< 0.1%
ValueCountFrequency (%)
1 3
 
< 0.1%
0 9997
> 99.9%

external_eef_organisation_type_top_nan
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0001
Minimum0
Maximum1
Zeros9999
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:47.486416image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01
Coefficient of variation (CV)100
Kurtosis10000
Mean0.0001
Median Absolute Deviation (MAD)0
Skewness100
Sum1
Variance0.0001
MonotonicityNot monotonic
2025-06-04T15:05:47.631065image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
0 9999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 9999
> 99.9%

external_eef_organisation_type_top_communications
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:47.765616image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:47.907835image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

external_eef_organisation_type_top_banking
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0003
Minimum0
Maximum1
Zeros9997
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:48.034211image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01731877577
Coefficient of variation (CV)57.72925255
Kurtosis3329.999
Mean0.0003
Median Absolute Deviation (MAD)0
Skewness57.71770092
Sum3
Variance0.000299939994
MonotonicityNot monotonic
2025-06-04T15:05:48.211413image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9997
> 99.9%
1 3
 
< 0.1%
ValueCountFrequency (%)
0 9997
> 99.9%
1 3
 
< 0.1%
ValueCountFrequency (%)
1 3
 
< 0.1%
0 9997
> 99.9%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:48.353313image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:48.496042image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

external_eef_organisation_type_top_defence
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:48.624815image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:48.787890image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:48.921289image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:49.043873image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:49.169830image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:49.290924image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

external_eef_organisation_type_top_transport & storage
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:49.433586image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:49.558211image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:49.720118image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:49.864341image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:49.984517image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:50.112214image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

external_eef_organisation_type_top_community services
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:50.228406image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:50.355954image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:50.514368image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:50.689543image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

external_eef_organisation_type_top_logistics
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0004
Minimum0
Maximum1
Zeros9996
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:50.885986image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01999699947
Coefficient of variation (CV)49.99249869
Kurtosis2496.24895
Mean0.0004
Median Absolute Deviation (MAD)0
Skewness49.97749193
Sum4
Variance0.000399879988
MonotonicityNot monotonic
2025-06-04T15:05:51.081950image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9996
> 99.9%
1 4
 
< 0.1%
ValueCountFrequency (%)
0 9996
> 99.9%
1 4
 
< 0.1%
ValueCountFrequency (%)
1 4
 
< 0.1%
0 9996
> 99.9%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:51.290868image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:51.464548image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

external_eef_organisation_type_top_telecommunication
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:51.613884image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:51.800896image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

external_eef_organisation_type_other
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:51.925060image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:52.036486image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0001
Minimum0
Maximum1
Zeros9999
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:52.179260image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01
Coefficient of variation (CV)100
Kurtosis10000
Mean0.0001
Median Absolute Deviation (MAD)0
Skewness100
Sum1
Variance0.0001
MonotonicityNot monotonic
2025-06-04T15:05:52.316666image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
0 9999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 9999
> 99.9%

project_prf_application_type_top_not recorded
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0001
Minimum0
Maximum1
Zeros9999
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:52.447161image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01
Coefficient of variation (CV)100
Kurtosis10000
Mean0.0001
Median Absolute Deviation (MAD)0
Skewness100
Sum1
Variance0.0001
MonotonicityNot monotonic
2025-06-04T15:05:52.605007image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
0 9999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 9999
> 99.9%

project_prf_application_type_top_nan
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0006
Minimum0
Maximum1
Zeros9994
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:52.783052image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02448877233
Coefficient of variation (CV)40.81462054
Kurtosis1662.499
Mean0.0006
Median Absolute Deviation (MAD)0
Skewness40.7941969
Sum6
Variance0.00059969997
MonotonicityNot monotonic
2025-06-04T15:05:52.915908image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9994
99.9%
1 6
 
0.1%
ValueCountFrequency (%)
0 9994
99.9%
1 6
 
0.1%
ValueCountFrequency (%)
1 6
 
0.1%
0 9994
99.9%

project_prf_application_type_top_unknown
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:53.048435image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:53.169892image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0001
Minimum0
Maximum1
Zeros9999
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:53.290967image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01
Coefficient of variation (CV)100
Kurtosis10000
Mean0.0001
Median Absolute Deviation (MAD)0
Skewness100
Sum1
Variance0.0001
MonotonicityNot monotonic
2025-06-04T15:05:53.433492image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
0 9999
> 99.9%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 9999
> 99.9%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:53.560577image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:53.689212image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:53.811987image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:53.936465image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

project_prf_application_type_top_business application
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:54.058656image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:54.177370image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:54.306723image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:54.415946image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

project_prf_application_type_top_online. esales
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:54.541726image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:54.668532image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:54.795357image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:54.931936image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:55.058358image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:55.183694image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:55.308765image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:55.434053image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:55.562205image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:55.686453image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

project_prf_application_type_top_document management
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:55.797220image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:55.935881image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:56.049486image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:56.181614image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:56.291656image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:56.428650image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

project_prf_application_type_top_data warehouse system
Real number (ℝ)

Constant  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:56.823015image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:56.947984image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:57.074037image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:57.206133image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros10000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:57.329897image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-04T15:05:57.453241image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%
ValueCountFrequency (%)
0 10000
100.0%

project_prf_application_type_other
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0152
Minimum0
Maximum1
Zeros9848
Zeros (%)98.5%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-04T15:05:57.579941image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1223538191
Coefficient of variation (CV)8.049593361
Kurtosis60.83592193
Mean0.0152
Median Absolute Deviation (MAD)0
Skewness7.926143753
Sum152
Variance0.01497045705
MonotonicityNot monotonic
2025-06-04T15:05:57.712198image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9848
98.5%
1 152
 
1.5%
ValueCountFrequency (%)
0 9848
98.5%
1 152
 
1.5%
ValueCountFrequency (%)
1 152
 
1.5%
0 9848
98.5%

tech_tf_clientserver_description
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

project_prf_development_type_not_defined
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

tech_tf_development_platform_hand_held
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

project_prf_relative_size_xxxl
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

tech_tf_architecture_multi_tier_client_server
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

tech_tf_client_server_not_applicable
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

tech_tf_type_of_server_proprietary_midrange
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

project_prf_application_type_top_transaction/production system
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

project_prf_application_type_top_financial application area
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB

project_prf_application_type_top_client-server
Unsupported

Missing  Rejected  Unsupported 

Missing10000
Missing (%)100.0%
Memory size78.3 KiB
Missing10000
Missing (%)100.0%
Memory size78.3 KiB